Tinjauan Sistematis Terhadap Algoritma Sistem Kekebalan Buatan (Artificial Immune System) dan Aplikasinya dalam Keamanan Siber

Rumadi Hartawan; Anton Zulkarnain Sianipar; Dyo Rizqal Fahlevi

Rumadi Hartawan STMIK Jayakarta
Anton Zulkarnain Sianipar STMIK Jayakarta
Dyo Rizqal Fahlevi STMIK Jayakarta

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Abstract

Sistem Kekebalan Buatan (Artificial Immune System / AIS) merupakan cabang dari Computational Intelligence yang terinspirasi oleh mekanisme imunologi biologis, seperti deteksi antigen, pembelajaran adaptif, dan memori imunologis. Penelitian ini menyajikan tinjauan sistematis terhadap perkembangan algoritma AIS serta penerapannya dalam bidang keamanan siber (cybersecurity). Kajian ini dilakukan dengan menganalisis berbagai publikasi terkini yang mencakup model dasar seperti Negative Selection Algorithm (NSA), Clonal Selection Algorithm (CSA), dan Artificial Immune Network (AIN), serta pendekatan baru seperti Symbiotic Artificial Immune System (SAIS). Hasil tinjauan menunjukkan bahwa AIS memiliki potensi tinggi dalam mendeteksi anomali, mengklasifikasikan ancaman, dan memperkuat sistem pertahanan adaptif terhadap serangan siber modern, termasuk malware, phishing, dan adversarial attacks. Namun demikian, tantangan utama masih terdapat pada efisiensi komputasi, skalabilitas, dan integrasi AIS dengan teknologi machine learning mutakhir. Artikel ini juga mengidentifikasi arah penelitian masa depan, seperti penggabungan AIS dengan paradigma deep learning dan federated security frameworks untuk menciptakan sistem deteksi ancaman yang lebih cerdas, cepat, dan otonom

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